The Economics of Enough_ How to Run the Economy as if the Future Matters - Diane Coyle [129]
What does this imply?
Switch resources in official statistical agencies away from the current focus on ever-more detailed aspects of the existing national accounts in order to:
• invest more in statistical research and innovation to address the conceptual gaps—in particular comprehensive wealth and measurement of intangibles;
• until comprehensive wealth accounts are available, develop a wider set of progress measures, drawing on an extensive public consultation on the Australian model;
• estimate and publish a thorough assessment of the true government debt burden, including correcting the frequently used accounting fudges and taking into account future implied pensions and welfare obligations;
• invest in new “satellite” accounts covering environmental impacts, household activities, and time use, and link them with conventional economic statistics;
• all of which will require ceasing collection and publication of decreasingly relevant statistics.
The last step alone will prove surprisingly hard, as it turns out that everything will have some users who’ll complain if they lose “their” statistics. But stopping painting a statistical portrait of the economy the old way will be almost as important as finding a new description. Historical statistics show that each economic epoch has its own character. Late Victorian statistics have a mass of detail on agricultural products, the legacy of an economy until recently dominated by food production, and a few figures on indicators of the new industrial economy, the length of rail tracks laid, number of factories, and exports of coal. By the 1930s, statistics covering the mass production industrial activities had taken the place of this rural portrait, but it wasn’t until the 1940s and 1950s that the current national accounts framework was put into place. This framework now needs to undergo a significant evolution again, and to release the resources to do this work, statistical agencies will need to cut some current areas of work to fund new ones.
As the historical experience shows, it takes some years, or even decades, for a new conceptual framework to replace an old one. The switch requires a transitional approach—the patterns revealed by partial new statistics will help the development of a new framework. The most important single contributory factor will be an acknowledgement on the part of governments and statisticians that the switch is needed, that the existing framework is no longer adequate for assessing the economy. While there is plenty of good work taking place in official statistical offices, there’s an understandable reluctance to concede that what’s in place now is no longer good enough. Much of the work needed—as, for example, on comprehensive wealth measurement, or obligations to future generations—is being undertaken by academic researchers. It will need the weight of officialdom behind it.
There’s a much greater problem in developing adequate statistics for poor economies, which have neither the money nor expertise to do so. Existing statistics are pretty poor anyway. Even where they exist, there’s great uncertainty as to their accuracy, given the means of collecting data. The gap that matters most for developing economies is the absence of comprehensive wealth measures, in order to demonstrate the almost-certainly shocking erosion of natural capital and absence of human and social capital in very poor countries. Such measures would lead to a marked change of perspective in policy development. In order to tackle the gap, innovations in technology and software will be needed to collect the necessary raw data. There are exciting examples showing the potential for the mobile phones and Internet applications to aggregate user-generated information. Existing applications include election monitoring and conflict reporting, but this is a promising and realistic